Safety first: a two-stage algorithm for the synthesis of reactive systems

In the game-theoretic approach to the synthesis of reactive systems, specifications are often expressed as ω-regular languages. Computing a winning strategy to an infinite game whose winning condition is an ω-regular language is then the main step in obtaining an implementation. Conjoining all the properties of a specification to obtain a monolithic game suffers from the doubly exponential determinization that is required. Despite the success of symbolic algorithms, the monolithic approach is not practical. Existing techniques achieve efficiency by imposing restrictions on the ω-regular languages they deal with. In contrast, we present an approach that achieves improvement in performance through the decomposition of the problem while still accepting the full set of ω-regular languages. Each property is translated into a deterministic ω-regular automaton explicitly while the two-player game defined by the collection of automata is played symbolically. Safety and persistence properties usually make up the majority of a specification. We take advantage of this by solving the game incrementally. Each safety and persistence property is used to gradually construct the parity game. Optimizations are applied after each refinement of the graph. This process produces a compact symbolic encoding of the parity game. We then compose the remaining properties and solve one final game after possibly solving smaller games to further optimize the graph. An implementation is finally derived from the winning strategies computed. We compare the results of our tool to those of the synthesis tool Anzu.     

A survey of partial-observation stochastic parity games

We consider two-player zero-sum stochastic games on graphs with ω-regular winning conditions specified as parity objectives. These games have applications in the design and control of reactive systems. We survey the complexity results for the problem of deciding the winner in such games, and in classes of interest obtained as special cases, based on the information and the power of randomization available to the players, on the class of objectives and on the winning mode. On the basis of information, these games can be classified as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided partial-observation (one player has partial-observation and the other player has complete-observation); and (c) complete-observation (both players have complete view of the game). The one-sided partial-observation games have two important subclasses: the one-player games, known as partial-observation Markov decision processes (POMDPs), and the blind one-player games, known as probabilistic automata. On the basis of randomization, (a) the players may not be allowed to use randomization (pure strategies), or (b) they may choose a probability distribution over actions but the actual random choice is external and not visible to the player (actions invisible), or (c) they may use full randomization. Finally, various classes of games are obtained by restricting the parity objective to a reachability, safety, Büchi, or coBüchi condition. We also consider several winning modes, such as sure-winning (i.e., all outcomes of a strategy have to satisfy the winning condition), almost-sure winning (i.e., winning with probability 1), limit-sure winning (i.e., winning with probability arbitrarily close to 1), and value-threshold winning (i.e., winning with probability at least ν, where ν is a given rational).     

From Parity Games to Circular Proofs

We survey on the ongoing research that relates the combinatorics of parity games to the algebra of categories with finite products, finite coproducts, initial algebras and final coalgebras of definable functors, i.e. μ-bicomplete categories.We argue that parity games with a given starting position play the role of terms for the theory of μ-bicomplete categories. We show that the interpretation of a parity game in the category of sets and functions is the set of deterministic winning strategies for one player in the game.We discuss bounded memory communication strategies between two parity games and their computational significance. We describe how an attempt to formalize them within the algebra of μ-bicomplete categories leads to develop a calculus of proofs that are allowed to contain cycles.     

Deciding co-observability is PSPACE-complete

In this note, we reduce the deterministic finite-state automata intersection problem to the problem of deciding co-observability for regular languages using a polynomial-time many-one mapping. This demonstrates that the problem of deciding co-observability for languages marked by deterministic finite-state automata is PSPACE-complete. We use a similar reduction to reduce the deterministic finite-state automata intersection problem to deciding other versions of co-observability introduced in a previous paper. These results imply that the co-observability of regular languages most likely cannot be decided in polynomial time unless we make further restrictions on the languages. These results also show that deciding decentralized supervisor existence is PSPACE-complete and therefore probably intractable.     

The complexity of constraint satisfaction games and QCSP

We study the complexity of two-person constraint satisfaction games. An instance of such a game is given by a collection of constraints on overlapping sets of variables, and the two players alternately make moves assigning values from a finite domain to the variables, in a specified order. The first player tries to satisfy all constraints, while the other tries to break at least one constraint; the goal is to decide whether the first player has a winning strategy. We show that such games can be conveniently represented by a logical form of quantified constraint satisfaction, where an instance is given by a first-order sentence in which quantifiers alternate and the quantifier-free part is a conjunction of (positive) atomic formulas; the goal is to decide whether the sentence is true.While the problem of deciding such a game is PSPACE-complete in general, by restricting the set of allowed constraint predicates, one can obtain infinite classes of constraint satisfaction games of lower complexity. We use the quantified constraint satisfaction framework to study how the complexity of deciding such a game depends on the parameter set of allowed predicates. With every predicate, one can associate certain predicate-preserving operations, called polymorphisms. We show that the complexity of our games is determined by the surjective polymorphisms of the constraint predicates. We illustrate how this result can be used by identifying the complexity of a wide variety of constraint satisfaction games.     

Concurrent reachability games

We consider concurrent two-player games with reachability objectives. In such games, at each round, player 1 and player 2 independently and simultaneously choose moves, and the two choices determine the next state of the game. The objective of player 1 is to reach a set of target states; the objective of player 2 is to prevent this. These are zero-sum games, and the reachability objective is one of the most basic objectives: determining the set of states from which player 1 can win the game is a fundamental problem in control theory and system verification. There are three types of winning states, according to the degree of certainty with which player 1 can reach the target. From type-1 states, player 1 has a deterministic strategy to always reach the target. From type-2 states, player 1 has a randomized strategy to reach the target with probability 1. From type-3 states, player 1 has for every real ε>0$\epsilon >0$ a randomized strategy to reach the target with probability greater than 1−ε$1-\epsilon$. We show that for finite state spaces, all three sets of winning states can be computed in polynomial time: type-1 states in linear time, and type-2 and type-3 states in quadratic time. The algorithms to compute the three sets of winning states also enable the construction of the winning and spoiling strategies.     

Flipping the winner of a poset game

Partially-ordered set games, also called poset games, are a class of two-player combinatorial games. The playing field consists of a set of elements, some of which are greater than other elements. Two players take turns removing an element and all elements greater than it, and whoever takes the last element wins. Examples of poset games include Nim and Chomp. We investigate the complexity of computing which player of a poset game has a winning strategy. We give an inductive procedure that modifies poset games to change the nim-value which informally captures the winning strategies in the game. For a generic poset game G, we describe an efficient method for constructing a game ¬G such that the first player has a winning strategy if and only if the second player has a winning strategy on G. This solves the long-standing problem of whether this construction can be done efficiently. This construction also allows us to reduce the class of Boolean formulas to poset games, establishing a lower bound on the complexity of poset games.     

Qualitative reachability in stochastic BPA games

We consider a class of infinite-state stochastic games generated by stateless pushdown automata (or, equivalently, 1-exit recursive state machines), where the winning objective is specified by a regular set of target configurations and a qualitative probability constraint ‘>0’ or ‘=1’. The goal of one player is to maximize the probability of reaching the target set so that the constraint is satisfied, while the other player aims at the opposite. We show that the winner in such games can be determined in P for the ‘>0’ constraint, and in NP∩co-NP for the ‘=1’ constraint. Further, we prove that the winning regions for both players are regular, and we design algorithms which compute the associated finite-state automata. Finally, we show that winning strategies can be synthesized effectively.     

Decision algorithms for multiplayer noncooperative games of incomplete information

Extending the complexity results of Reif [1,2] for two player games of incomplete information, this paper (see also [3]) presents algorithms for deciding the outcome for various classes of multiplayer games of incomplete information, i.e., deciding whether or not a team has a winning strategy for a particular game. Our companion paper, [4] shows that these algorithms are indeed asymptotically optimal by providing matching lower bounds. The classes of games to which our algorithms are applicable include games which were not previously known to be decidable. We apply our algorithms to provide alternative upper bounds, and new time-space trade-offs on the complexity of multiperson alternating Turing machines [3]. We analyze the algorithms to characterize the space complexity of multiplayer games in terms of the complexity of deterministic computation on Turing machines.In hierarchical multiplayer games, each additional clique (subset of players with the same information) increases the complexity of the outcome problem by a further exponential. We show that an S(n) space bounded k-player game of incomplete information has a deterministic time upper bound of k + 1 repeated exponentials of S(n). Furthermore, S(n) space bounded k-player blindfold games have a deterministic space upper bound of k repeated exponentials of S(n). This paper proves that this exponential blow-up can occur.We also show that time bounded games do not exhibit such hierarchy. A T(n) time bounded blindfold multiplayer game, as well as a T(n) time bounded multiplayer game of incomplete information, has a deterministic space bound of T(n).     

Test selection based on communicating nondeterministic finite-statemachines using a generalized Wp-method

Presents a method of generating test sequences for concurrent programs and communication protocols that are modeled as communicating nondeterministic finite-state machines (CNFSMs). A conformance relation, called trace-equivalence, is defined within this model, serving as a guide to test generation. A test generation method for a single nondeterministic finite-state machine (NFSM) is developed, which is an improved and generalized version of the Wp-method that generates test sequences only for deterministic finite-state machines. It is applicable to both nondeterministic and deterministic finite-state machines. When applied to deterministic finite-state machines, it yields usually smaller test suites with full fault coverage than the existing methods that also provide full fault coverage, provided that the number of states in implementation NFSMs are bounded by a known integer. For a system of CNFSMs, the test sequences are generated in the following manner: a system of CNFSMs is first reduced into a single NFSM by reachability analysis; then the test sequences are generated from the resulting NFSM using the generalized Wp-method     

Improving behavior of computer game bots using fictitious play

In modern computer games, "bots" - intelligent realistic agents play a prominent role in the popularity of a game in the market. Typically, bots are modeled using finite-state machine and then programmed via simple conditional statements which are hard-coded in bots logic. Since these bots have become quite predictable to an experienced games player, a player might lose interest in the game. We propose the use of a game theoretic based learning rule called fictitious play for improving behavior of these computer game bots which will make them less predictable and hence, more a enjoyable game.     

扰动值模糊有限自动机及其语言*

引入扰动值模糊有限自动机及其语言的概念,讨论扰动值模糊有限自动机的状态转移函数的扩张问题,证明3类确定型扰动值模糊有限自动机、非确定型扰动值模糊有限自动机相互等价性,研究扰动值模糊有限自动机的语言关于正则运算的封闭性.     

Constructive semantics for instantaneous reactions

This paper presents some results towards a game-theoretic account of the constructive semantics of step responses for synchronous languages, providing a coherent semantic framework encompassing both non-deterministic Statecharts (as per Pnueli & Shalev) and deterministic esterel. In particular, it is shown that esterel arises from a finiteness condition on strategies whereas Statecharts permits infinite games. Beyond giving a novel and unifying account of these concrete languages the paper sketches a general theory for obtaining different notions of constructive responses in terms of winning conditions for finite and infinite games and their characterisation as maximal post-fixed points of functions in directed complete lattices of intensional truth-values.     

Games with Uniqueness Properties

For two-player games of perfect information such as Checkers, Chess, and Go we introduce uniqueness properties. A game position has a uniqueness property if a winning strategy—should one exist—is forced to be unique. Depending on the way that winning strategy is forced, a uniqueness property is classified as weak, strong, or global. We prove that any reasonable two-player game G is extendable to a game G ^* with the strong uniqueness property for both players, so that, e.g., QBF remains PSPACE-complete under this reduction. For global uniqueness, we introduce a simple game over Boolean formulas with this property, and prove that any reasonable two-player game with the global uniqueness property is reducible to it. We show that the class of languages that reduce to globally unique games equals Niedermeier and Rossmaniths unambiguous alternation class UAP, which is in an interesting region between FewP and SPP.     

Noise and the magic square game

A pseudo-telepathy game is a game for two or more players for which there is no classical winning strategy, but there is a winning strategy based on sharing quantum entanglement by the players. Since it is generally very hard to perfectly implement a quantum winning strategy for a pseudo-telepathy game, quantum players are almost certain to make errors even though they use a winning strategy. After introducing a model for pseudo-telepathy games, we investigate the impact of erroneously performed unitary transformations and also of noisy measurement devices on the quantum winning strategy for the magic square game. The question of how strong both types of noise can be so that quantum players would still be better than classical ones is also dealt with.     

Dynamic hierarchical reactive controller synthesis

In the formal approach to reactive controller synthesis, a symbolic controller for a possibly hybrid system is obtained by algorithmically computing a winning strategy in a two-player game. Such game-solving algorithms scale poorly as the size of the game graph increases. However, in many applications, the game graph has a natural hierarchical structure. In this paper, we propose a modeling formalism and a synthesis algorithm that exploits this hierarchical structure for more scalable synthesis. We define local games on hierarchical graphs as a modeling formalism that decomposes a large-scale reactive synthesis problem in two dimensions. First, the construction of a hierarchical game graph introduces abstraction layers, where each layer is again a two-player game graph. Second, every such layer is decomposed into multiple local game graphs, each corresponding to a node in the higher level game graph. While local games have the potential to reduce the state space for controller synthesis, they lead to more complex synthesis problems where strategies computed for one local game can impose additional requirements on lower-level local games. Our second contribution is a procedure to construct a dynamic controller for local game graphs over hierarchies. The controller computes assume-admissible winning strategies that satisfy local specifications in the presence of environment assumptions, and dynamically updates specifications and strategies due to interactions between games at different abstraction layers at each step of the play. We show that our synthesis procedure is sound: the controller constructs a play that satisfies all local specifications. We illustrate our results through an example controlling an autonomous robot in a building with known floor plan and provide simulation results using an implementation of our algorithm on top of LTLMoP.     

Reduction of stochastic parity to stochastic mean-payoff games

A stochastic graph game is played by two players on a game graph with probabilistic transitions. We consider stochastic graph games with ω-regular winning conditions specified as parity objectives, and mean-payoff (or limit-average) objectives. These games lie in NP ∩ coNP. We present a polynomial-time Turing reduction of stochastic parity games to stochastic mean-payoff games.     

Strategy construction for parity games with imperfect information

We consider two-player parity games with imperfect information in which strategies rely on observations that provide imperfect information about the history of a play. To solve such games, i.e., to determine the winning regions of players and corresponding winning strategies, one can use the subset construction to build an equivalent perfect-information game. Recently, an algorithm that avoids the inefficient subset construction has been proposed. The algorithm performs a fixed-point computation in a lattice of antichains, thus maintaining a succinct representation of state sets. However, this representation does not allow to recover winning strategies.In this paper, we build on the antichain approach to develop an algorithm for constructing the winning strategies in parity games of imperfect information. One major obstacle in adapting the classical procedure is that the complementation of attractor sets would break the invariant of downward-closedness on which the antichain representation relies. We overcome this difficulty by decomposing problem instances recursively into games with a combination of reachability, safety, and simpler parity conditions. We also report on an experimental implementation of our algorithm; to our knowledge, this is the first implementation of a procedure for solving imperfect-information parity games on graphs.     

State complexity of basic operations on suffix-free regular languages

We investigate the state complexity of basic operations for suffix-free regular languages. The state complexity of an operation for regular languages is the number of states that are necessary and sufficient in the worst-case for the minimal deterministic finite-state automaton that accepts the language obtained from the operation. We establish the precise state complexity of catenation, Kleene star, reversal and the Boolean operations for suffix-free regular languages.